Software Engineer, Developer Productivity

Other

• Develop and maintain our Bazel monorepo with support for multiple languages.
• Improve build hermeticity, caching, reproducibility, and dependency management.
• Extend Bazel with custom rules, macros, and integrations.
• Operate and optimize pipelines on GitHub Actions, Kubernetes, and cloud runners.
• Reduce CI latency through remote execution, caching, and parallelization.
• Instrument pipelines with telemetry and dashboards to measure speed, reliability, and cost.
• Build tools and workflows (CLI utilities, IDE plugins, GitHub bots) that improve day-to-day developer experience.
• Automate debugging of flaky tests and CI failures.
• Simplify onboarding and local dev environments.
• Enable engineers to integrate AI-powered coding assistants (e.g. GitHub Copilot, Cursor, Claude) into daily workflows.
• Build agentic tooling that automates CI failure analysis, PR triage, and code review support.
• Collect usage insights, build dashboards, and iterate on adoption strategies to maximize developer ROI from AI.
• You’ll work on critical build and CI/CD systems that touch every engineer’s workflow.
• You’ll have a direct impact on the speed, reliability, and cost of software delivery.
• You’ll be at the frontier of AI adoption in engineering teams, shaping how humans and AI collaborate in development.
• You’ll have opportunities to contribute to open source (Bazel, rules projects, CI tooling) and share learnings at conferences
• Strong software engineering background (Java, Go, Python, or similar).
• Experience with build systems (Bazel strongly preferred; Buck, Blaze, Gradle, or Maven acceptable).
• Hands-on with CI/CD systems (GitHub Actions, Buildkite, Jenkins, etc.).
• Familiarity with Docker/Kubernetes, cloud runners, and distributed build/test environments.
• Experience integrating or enabling AI developer tools is a plus.
• Strong debugging skills and an interest in solving workflow bottlenecks.
• Passion for multiplying the effectiveness of other engineers.
• This role is hybrid (4 days a week in our Mountain View office)